使用多通道睡眠記錄儀器（polysomnogram, PSG）量測睡眠訊號是現今主要的量測方式，包含腦電訊號(EEG)、眼動電訊號(EOG)與肌電訊號(EMG)。但主要判讀睡眠階段的依據是EEG，因此為了簡化量測而出現單通道EEG量測睡眠的方式。EEG不僅是應用於量測睡眠，還可以應用於量測其它大腦活動，如神經回饋訓練中，用來當作回饋的訊號來源。並且除了PSG外，還可以使用其他放大器，如SynAmps2，來傳導訊號。但由於量測時使用者需要帶上電極帽，並且接電極線到放大器再傳導到電腦上。這種複雜的儀器設備讓使用者無法自行操作，而且需要專業人士輔助，還可能會干擾使用者睡眠，使得量測結果有偏差。因此我們希望能夠找到一個方便讓使用者自行操作的電極安置方式，並且從這個位置量測到的訊號要與EEG相似。
我們將電極點放置在前額上的不同位置，因為前額讓使用者較為容易自己使用，並且量測睡眠與alpha神經回饋訓練的特徵：alpha (8-12Hz)、spindle (12-14Hz)與delta (0.5-2Hz)來確認將要使用的電極點位置是否適合。首先將透過兩次神經回饋訓練收取到的訊號在前額位置上的表現與分析的結果決定出一個前額的電極擺放位置，再量測睡眠訊號，確定前額位置對於睡眠與神經回饋訓練的表現。
經由實驗結果，我們可以確定前額位置能夠量測到睡眠與神經回饋訓練。在未來或許能夠應用於穿戴式裝置，使得量測睡眠與神經回饋訓練更加便利；或是應用到其它的方面，如偵測癲癇、治療失眠的神經回饋訓練或是大腦事件相關電位(brain event-related potential)。

A multi-channel polysomnogram (PSG), recording include an electroencephalogram (EEG), an electrooculogram (EOG) and an electromyogram (EMG), is a clinically approved sleep-monitoring device, the recording includes EEG, EOG, and EMG. But on sleep analysis, the staging is based on EEG, EOG and EMG are auxiliary. So in order to simplify the measurement, a single channel EEG was developed for sleep staging. EEG is not only used in measuring sleep but also can be used in measuring other brain activities, such as neurofeedback training (NFT). And in addition to PSG, other amplifiers, such as SynAmps2, can be used to record signals. However, due to that users need to wear the electrode cap, which sends signals to an amplifier via electrode wires and operate the instrument with the professional help. It may cause sleep disturbance and may bias measurement of sleep quality. Thus, we want to find the electrodes placement that users can easily operate by their own, and the signal from this placement will be similar to the EEG.
Placed the electrodes in different positions on the forehead, because that it is easier for the users to operate on their own, and then had nine bipolar forehead channels. Measured the patterns of sleep and alpha NFT - alpha (8-12Hz), spindle (12-14Hz) and delta (0.5 to 2 Hz) to confirm that the electrodes placement to be used is appropriate. First of all, through the recordings of forehead channels from two neural feedback training, we analyzed the result of each channel and determined which will be used. Then used the determined forehead channel in sleep-monitoring, and compared the results with EEG.
Through the results of the experiments, we can observe that the determined forehead channel could use in measurement the patterns of sleep and NFT. And in the future, the forehead channel may be able to apply in the wearable device, which can ease the way of measurement. Or the forehead channel may be able to apply in other application, such as detection of epilepsy, treatment of insomnia, or brain event-related potential.

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